Decoding the molecular landscape of the placenta in maternal diabetes: a systematic review of high-throughput data

Georgia Fakonti1, Abigail R Byford1, Eleanor M Scott2

  • 1Discovery and Translational Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.

Diabetes in pregnancy is associated with significant short- and long-term complications for mothers and offspring, many of which are thought to result from altered placental development and function. Although studies have demonstrated molecular changes in the placenta in this context, the precise mechanisms remain unclear. High-throughput transcriptomic and proteomic approaches provide powerful tools to systematically identify disease-associated pathways, yet no systematic synthesis of this literature has been undertaken. We conducted a systematic review of omics studies examining placental molecular changes in pregnancies complicated by diabetes compared with uncomplicated pregnancies. Fifty-six studies were eligible for inclusion, the majority of which focused on gestational diabetes mellitus (GDM; n = 52). Of these, 42 reported changes in RNA (n = 30) or protein (n = 12) abundance, with eight proteins and 189 RNA species consistently altered in at least two studies. Functional enrichment analysis revealed dysregulation of immune, vascular, and developmental pathways. Notably, 98 molecules were altered at both RNA and protein levels, 47 with consistent directionality across studies, suggesting robust disruption of core biological pathways. Comparisons across diabetes types showed partial overlap of differentially expressed transcripts between GDM and type 1 diabetes (16 genes) and GDM and type 2 diabetes (34 genes), although no universal markers were identified. These findings highlight shared molecular signatures in GDM, provide novel insights into pathways linking maternal diabetes to placental dysfunction and adverse outcomes, and emphasise the need for further studies on type 1 and type 2 diabetes. These pathways may represent potential therapeutic targets to mitigate intergenerational cardiometabolic risk.

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